The present invention relates to systems and methods for analyzing textural features in biological samples. More specifically, the present invention relates to systems and methods for analyzing target contrast features in digital images of biological samples.
Analysis of textural features in biological specimens is desirable in a wide range of applications. It is often useful to have a quantitative measurement of the occurrence of a defined structural element in a biological sample, as well as a quantitative comparison between two samples of the occurrence of a feature.
There is a current need in drug discovery and development, as well as general biological research, to quickly and accurately image and analyze textural features in a large numbers of biological samples. This need has largely arisen in the pharmaceutical industry where it is common to test chemical compounds for activity against a variety of biochemical targets (e.g., receptors, enzymes, and nucleic acids).
Many current techniques for determining structure and texture in biological specimens require significant manual intervention or complex, time-intensive computation.
Accordingly, given the need for imaging large numbers of samples which frequently results in a large amount of data, it would be desirable to provide rapid methods for analyzing images of samples shortly after their acquisition. It would also be desirable to complete analysis of images quickly enough so as to not slow down data acquisition.
It would further be desirable to provide systems and methods for rapid analysis of target contrast features in images of biological samples.
The present invention relates to systems and methods for rapidly identifying contrast features of specific size and contrast in digital images of biological samples that may have varying backgrounds. The present invention may efficiently search an image for object seed points in a target contrast feature, make decisions in the analysis procedure as to whether to further consider a. local region or to move to the next region, and if a region is evaluated, to use selected portions in calculating parameters to qualify the contrast feature as a grain.
The present invention may analyze two dimensional, three dimensional, or other suitable multi-dimensional images. Images may be acquired, for example, by using fluorescence imaging, fluorescence polarization imaging, dark field imaging, bright field transmission imaging, phase contrast imaging, differential interference contrast imaging, or any other suitable imaging technique or image acquisition system after which analysis by the present invention may ensue.
Contrast features analyzed by the present invention may be comprised of small clusters of pixels that are either higher or lower in intensity than the pixels that surround them. In some embodiments, parameters may be tuned to locate contrast features whose characteristic size or intensity level correspond to features having significance in a given application. Contrast features that meet size or intensity requirements may be classified as grains (textural features).
For example, contrast features may be analyzed using the systems and methods of the present invention to determine cell surface receptor internalization, nuclear chromatin condensation, localization to intracellular compartments that produce a punctate staining pattern (e.g., mitochondria or golgi), localization to any vesicle, pit, lysosome or endosome either within a cell or on the cell surface, any endocytosis, exocytosis or degranulation event whereby matter is internalized or released from a cell via vesicular structures, or any other suitable determination from an image of a biological sample.
In some embodiments, the present invention may calculate the number of grains found in a region of interest, the number of grains found in an image, the number of grains found in a biological sample, the number of grains per unit area, the ratio of grain intensity to image intensity, the average grain intensity, the area fraction occupied by grains, any combination thereof, or any other suitable computation.